Toward a Data‐Effective Calibration of a Fully Distributed Catchment Water Quality Model.

Distributed hydrological water quality models are increasingly being used to manage natural resources at the catchment scale but there are no calibration guidelines for selecting the most effective gauging stations. In this study, we investigated the influence of calibration schemes on the spatiotemporal performance of a fully distributed process‐based hydrological water quality model (mHM‐Nitrate) for discharge and nitrate simulations at the Bode catchment in central Germany. We used a single‐ and two multi‐site calibration schemes where the two multi‐site schemes varied in number of gauging stations but each subcatchment represented different dominant land uses of the catchment. To extract a set of behavioral parameters for each calibration scheme, we chose a sequential multi‐criteria method with 300,000 iterations. For discharge (Q), model performance was similar among the three schemes (NSE varied from 0.88 to 0.92). However, for nitrate concentration (NO3− ${\mathit{NO}}_{3}^{\mathit{-}}$), the multi‐site schemes performed better than the single site scheme. This improvement may be attributed to that multi‐site schemes incorporated a broader range of data, including low Q and NO3− ${\mathit{NO}}_{3}^{\mathit{-}}$ values, thus provided a better representation of within‐catchment diversity. Conversely, adding more gauging stations in the multi‐site approaches did not lead to further improvements in catchment representation but showed wider 95% uncertainty boundaries. Thus, adding observations that contained similar information on catchment characteristics did not seem to improve model performance; however, it increased uncertainty. These results highlight the importance of strategically selecting gauging stations that reflect the full range of catchment heterogeneity rather than seeking to maximize station number, to optimize parameter calibration. Plain Language Summary: Water quality management in catchment areas is crucial for maintaining the health of aquatic ecosystems and ensuring safe drinking water. Catchment hydrological water quality models have become valuable tools for predicting and managing water quality in complex catchment systems. Typically, these models are calibrated using data from a single site (at the outlet), assuming that this location represents the entire catchment. However, recent studies have shown contrasting findings regarding the performance of hydrological water quality models calibrated at a single site versus multiple sites. To address this issue, the study focuses on achieving effective calibration of a fully distributed catchment water quality model known as mHM‐Nitrate. This study investigates the impacts of multi‐site calibration compared to single‐site calibration on the model's accuracy in estimating nitrate concentration at non‐calibrated locations within a heterogenous catchment. By comparing different calibration schemes and analyzing the model's performance in estimating nitrate concentration at non‐calibrated stations, the study highlights the importance of incorporating multi‐site calibration in a data‐effective manner to enhance the reliability and accuracy of catchment water quality models. The findings have important implications for the design of monitoring networks and the selection of calibration data, ultimately contributing to more effective water quality management strategies. Key Points: Single‐ and multi‐site calibration approaches generally led to similar model performance for discharge (Q) at the catchment outletInfluence of calibration stations on the spatiotemporal performance of a fully distributed process‐based hydrological water quality modelQuality of the nitrate simulation depends on representativeness of their catchment characteristics than the number of calibration stations [ABSTRACT FROM AUTHOR]